Although American men of European ancestry represent the largest population of patients with prostate cancer, men of African ancestry are disproportionately affected by prostate cancer, with higher prevalence and worse outcomes. These racial disparities in prostate cancer are due to multiple factors, but variations in genomic susceptibility such as SNP may play an important role in determining cancer aggressiveness and treatment outcome. Using public databases, we have identified a prostate cancer susceptibility SNP at an intronic enhancer of the neural precursor expressed, developmentally downregulated 9 (NEDD9) gene, which is strongly associated with increased risk of patients with African ancestry. This genetic variation increased expression of NEDD9 by modulating the chromatin binding of certain transcription factors, including ERG and NANOG. Moreover, NEDD9 displayed oncogenic activity in prostate cancer cells, promoting prostate cancer tumor growth and metastasis in vitro and in vivo. Together, our study provides novel insights into the genetic mechanisms driving prostate cancer racial disparities.
A prostate cancer susceptibility genetic variation in NEDD9, which is strongly associated with the increased risk of patients with African ancestry, increases NEDD9 expression and promotes initiation and progression of prostate cancer.
See related commentary by Mavura and Huang, p. 3764
Prostate cancer is one of the leading causes of cancer-related death in American men. The incidence and mortality of prostate cancer are greater in men of African ancestry (AA) than European ancestry (EA; ref. 1). Although some of these disparities may be due to socioeconomic differences, the genetic differences between these racial subgroups also play an important role in determining the cancer aggressiveness and the outcome of the treatments (1–3). Through analyses of public databases, our previous study has identified a small panel of prostate cancer risk-associated SNPs with significant differences of allele frequency in African men versus non-African men (4). The top-ranked SNP, rs4713266, located at an intronic region of the neural precursor expressed, developmentally downregulated 9 (NEDD9) gene (5) was also previously identified in a large prostate cancer genome-wide association study (GWAS) analysis (6), and the frequency of the risk allele is significantly increased in AA men.
NEDD9 encodes a member of the Cas family of signaling transduction molecules, which is a noncatalytic focal adhesion protein phosphorylated by FAK and Src and functions as a signaling hub to regulate downstream signaling, such as the AKT pathway. In cancers, NEDD9 regulates cell migration, epithelial–mesenchymal transition (EMT), invasion, and metastasis (7–10). Importantly, gene amplification of NEDD9 is commonly found in the advanced metastatic castration-resistant prostate cancer (CRPC; ∼3%) and neuroendocrine prostate cancer (NEPC; ∼15%; refs. 11, 12), suggesting NEDD9 may play an important role in prostate cancer progression.
The intronic region of NEDD9 that harbors rs4713266 is highly enriched for enhancer histone marks, indicating that this chromatin region may contain a putative enhancer. Using the CRISPR editing method to modify the nucleotide of rs4713266 in prostate cancer cells, we show that NEDD9 expression was increased by converting the nonrisk variant (T) to the risk variant (C). Mechanistically, we demonstrated that this genetic variation altered the binding and activity of multiple transcription factors (TF), including ERG and NANOG. Although a NEDD9 germline variant has been reported being associated with prostate cancer susceptibility (6), and NEDD9 is thought to regulate EMT and invasion in prostate cancer cells (10), it remains unclear whether NEDD9 is involved in prostate cancer development in vivo. Using VCaP and MDA-PCa-2b prostate cancer cell line models, we found that silencing NEDD9 repressed cell growth, migration, and invasion in vitro, and tumor growth and metastasis in vivo. Overall, our results indicate that increased expression of NEDD9 by the genetic variation of rs4713266 may drive prostate cancer initiation and progression in AA men.
Materials and Methods
Cell line and cell culture
VCaP, CWR22-RV1, LNCaP, PC3, and MDA-PCa-2b cell lines were purchased from the ATCC, were authenticated every 6 months using short tandem repeat profiling, and tested for mycoplasma contamination using the MycoAlert mycoplasma detection Kit (Lonza). VCaP and its derived stable cell lines were cultured in DMEM supplemented with 10% FBS (Gibco). CWR22-RV1 and its isogenic stable lines and LNCaP-derived stable cell lines were cultured in RPMI-1640 medium with 10% FBS. PC3 cells were cultured in F-12K medium with 10% FBS. MDA-PCa-2b cells were cultured in BRFF-HPC1 medium with 20% FBS.
For the preparation of chromatin immunoprecipitation (ChIP), dispensed cells were formalin-fixed, lysed, and sonicated to break the chromatin into 500 to 800 bp fragments, followed by immunoprecipitation with ChIP grade antibodies: anti-H3K4me1 (ab8895, Abcam), anti-H3K4me2 (07-030, Millipore), anti-H3K27ac (ab4729, Abcam), anti–p-Pol2-S5 (ab5131, Abcam), anti-ERG (ab110639, Abcam), anti-HA (ab9110, Abcam), and Rabbit/Mouse IgG (Millipore). The qPCR analysis was carried out using the SYBR Green method on QuantStudio 3 Real-time PCR system (Thermo Fisher Scientific). The primers for KLK3-Enh were previously listed (13), and other primers are NEDD9-Int1Enh Forward: 5′-AGGGTGAAATTGTTGTACTTAGAGA-3′, Reverse: 5′-TCCTGCTGTCTGTCTCCCAT-3′; NEDD9-S1 (ERG-binding site) Forward: 5′-AAGCCTCACAGCCAGAGACT-3′, Reverse: 5′-CCGATCTGCGTCATTATCCT-3′; NEDD9-S2 (ERG-binding site) Forward: 5′-ATGTCCAAGTCACTCAAGCC-3′, Reverse: 5′-TTTAAATAGGGAGGGGCAGGC-3′.
RT-PCR and immunoblotting
The expression of mRNA was measured using real-time RT-PCR analyses with Taqman Fast one-step Mix RT-PCR reagents (Thermo Fisher Scientific) on QuantStudio 3 Real-time PCR system. The results were normalized to coamplified GAPDH. The primer and probe sets for NEDD9, ERG, NANOG, and GAPDH were purchased as an inventoried mix from Applied Biosystems (Thermo Fisher Scientific). For immunoblotting, cells were lysed with RIPA buffer containing protease inhibitor cocktail (Thermo Fisher Scientific) and anti-ERG (ab110639, Abcam), anti-NEDD9 (ab18056, Abcam), anti-NANOG (3580, Cell Signaling Technology), anti–pAkt S473 (4060, Cell Signaling Technology), anti-Akt (9272, Cell Signaling Technology), anti-HA (H3663, Sigma), and anti-GAPDH (ab8245, Abcam) were used. Immunoblotting results shown are representative of at least three independent experiments.
For the CRISPR gene activation approach, CWR22-RV1 cells were stably infected with lentiviral dCas9-VPR, which expresses catalytically deactivated Cas9 fused to VP64, p65, and Rta transcription activator complex (Dharmacon), followed by blasticidin selection. The established stable cells were then infected with the lentiviral sgRNAs (52963, Addgene): sg-266 against the rs4713266 region (5′-AGTCACTCAAGCCTCACAGC-3′); sg-334 against the rs2018334 region (5′-GAAGGAACTTTAAACAATTA-3′); sg-NE against a nearby nonenhancer region (5′-CCGCACTGCTTAACACTCTC-3′), followed by puromycin selection.
For the CRISPR deletion approach, Cas9-expressing parental CWR22-RV1 cells were generated by stably infecting CWR22-RV1 cells with lentiviral Cas9-expressing vector (52962, Addgene) and selected with blasticidin. The cells were then stably infected with a pair of lentiviral sgRNAs (52963, Addgene) targeting the 5′ and 3′ boundary sequences of NEDD9-Int1Enh (sg-Int1Enh-5′: 5′-TAACAGCCAAATGAATTTCA-3′; sg-Int1Enh-3′: 5′-CCAACTCCTCCCTGCCTTTT-3′), followed by puromycin selection.
For the CRISPR nucleotide editing approach, Cas9-expressing CWR22-RV1 cells were first transfected with a single-strand DNA template that contains a 60-nucleotide fragment of either the nonrisk T allele or risk C allele for 24 hours and then infected with a lentiviral sgRNA (Dharmacon) targeting rs4713266 site (5′-AGCCTCACAGCCAGAGACTA-3′), followed by puromycin selection. Colonies were then screened for genotyping of rs4713266. Cell clones with unsuccessful editing were selected as control lines (C/T heterozygous).
RNAi and transfection
siRNAs against NEDD9, ERG, NANOG, and nontarget control (NTC) were directly purchased (ON-TARGETplus, Dharmacon). The transfection reagent used in this study was lipofectamine 2000 (Thermo Fisher Scientific). VCaP-shNEDD9 and VCaP-shNTC cells were generated by stable infection of lentiviral shRNA against NEDD9 or NTC (Dharmacon), followed by puromycin selection and confirmation for NEDD9 expression.
For RNA sequencing (RNA-seq) analysis, VCaP-shNTC and VCaP-shNEDD9 cells were harvested for RNA extraction and followed by RNA-seq library preparation with the TruSeq Stranded RNA LT Kit (Illumina). Sequencing was performed on HiSeq 2500 Illumina Genome Analyzer. The single-end reads were processed by FastQC and aligned by STAR (version 2.5; ref. 14) to the human Ensemble genome (Ensembl, GRCh38) with all default parameters. featureCounts (15) from Subread package was used to assign sequence reads to the genomic features. edgeR (16) was used for differential expression analysis, and the list of differentially expressed genes was generated using 2-fold cutoff and P < 0.01 (FDR). The Gene Expression Omnibus accession for RNA-seq is GSE164531.
Cell proliferation assay
Cells were stained with the Muse Count & Viability Assay Kit for 5 minutes and then counted by Muse Cell Analyzer (EMD Millipore).
Luciferase reporter assay
The reporters were created by inserting approximately 300 or 800 bp DNA fragments around rs4713266 (C or T allele), or approximately 800 bp DNA fragment around rs2018334 (G or A allele) into a pGL3 Firefly luciferase reporter vector containing a minimum promoter (E1761, Promega). PC3 cells were then transfected with these reporters, ERG- or NANOG-expressing pcDNA3.1 plasmid, and a Renilla luciferase reporter. The activities of Firefly luciferase and Renilla luciferase were measured using the dual-luciferase reporter assay (Promega), and the results were normalized for Renilla activities.
VCaP-shNTC and VCaP-shNEDD9 xenograft tumors were established in the flanks of castrated male SCID mice (4–6 weeks) by injecting approximately 2 million cells mixed with 50% Matrigel. Tumor volume was measured by manual caliper using the formula V = (W2 × L)/2. All animal experiments were approved by the UMass Boston Institutional Animal Care and Use Committee (IACUC) and were performed following institutional and national (U.S.) guidelines. The housing conditions were ambient temperatures of 65 to 75°F with 40% to 60% humidity and 12-hour light/12-hour dark cycle.
Invasion assays were performed with Corning BioCoat Matrigel Invasion Chambers (354480, Corning). Per the manufacturer's protocol, in brief, the same number of VCaP cells was seeded in the premoisturized upper chamber with serum-free medium, and the lower chamber was filled with medium containing 10% FBS as the chemoattractant. After 3 days, noninvading cells were removed by cotton swab, and the invaded cells were fixed with 100% methanol and then stained with Giemsa staining solution (Fisher). All experiments were done in biological triplicates, and images were taken by EVOS auto fluorescence microscope (Thermo Fisher Scientific).
Transwell migration assays were performed with Corning FluoroBlok Inserts (351152, Corning). Per the manufacturer's protocol, the same number of MDA-PCa-2b cells was seeded in the premoisturized upper chamber with serum-free medium, and the lower chamber was filled with medium containing 20% FBS as a chemoattractant. After 2 days, migrated cells were stained by Corning Calcein AM Fluorescent Dye (354217, Corning). All experiments were done in biological triplicates, and images were taken by EVOS auto fluorescence microscope.
Zebrafish embryo metastasis assay
Embryos were produced from AB and TUE wild-type zebrafish lines by natural spawning. All experiments were performed in 2- to 3-day postfertilization embryos following an IACUC-approved protocol. Cell injections were performed as previously described (17, 18). In brief, 2 dpf embryos were dechorionated and anesthetized with 0.04 mg/mL tricaine, and approximately 100 GFP-expressing cells were microinjected into the perivitelline space of each embryo using a borosilliac micropipette. After injection, embryos were washed to remove tricaine and then maintained in 96-well plates at 28°C. Embryos were imaged immediately after injection and then every hour till up to 24 hours.
The database of TF-binding motifs was downloaded from Jaspar. To identify potential TFs that may favor the binding to the risk allele of rs4713266 region, we used MotifDb R package. Each TF was scanned using their corresponding positions weight matrix to match the DNA region (including the complementary strand sequence) with a length of 4, 5, and 6 for T/C nucleotide (risk and nonrisk alleles) and ranked by calculating the ratio of the matching score on the risk (cutoff >0.8) versus nonrisk allele. The TFs that bind similarly to both risk and nonrisk alleles were then removed.
Data in bar graphs represent mean ± SD of at least three biological repeats. Statistical analyses were generally performed using unpaired two-tailed Student t test by comparing treatment versus vehicle control or otherwise as indicated. P value < 0.05 (*) was considered to be statistically significant. For animal studies, a two-tailed Student t test was performed to determine the statistical difference of tumor growth at the final time point.
Identification of rs4713266 as the top-ranked AA-associated prostate cancer risk SNP
Our previous analyses using several public databases including GWAS have identified a list of 38 SNPs (Supplementary Fig. S1) that are associated with increased prostate cancer susceptibility and also have greater risk allele frequencies in African versus non-African populations (4). We then reranked these SNPs based on the correlation with prostate cancer incidences in three racial groups from two studies (gnomAD and 1000Genomes) and identified rs4713266 (risk allele genotype C, nonrisk allele genotype T) as the top-ranked AA-associated SNP (Fig. 1A). This SNP falls in a recently reported susceptibility locus of prostate cancer at the chromatin region 6p24.2, which is located at an intronic region of the NEDD9 gene (6). The frequency of risk alleles (∼80% in AA, ∼50% in EA, and ∼20% in East Asian men) significantly correlates with the prostate cancer incidence and aggressiveness of racial subgroups. Susceptibility loci often contain multiple linkage disequilibrium (LD) variants. Using the HaploReg tool, we also identified a nearby rs2018334 (∼1 kb apart) as the LD variant of rs4713266 (r2 = 0.99), which is also highly correlated with the racial disparity in prostate cancer incidence (19).
The intronic region that contains these two SNPs is highly enriched for multiple enhancer marks, including H3K4me1/2, H3K27ac, and DNase hypersensitivity (19), suggesting it may be a putative enhancer of the NEDD9 gene. Searching public datasets of eQTL (expression quantitative trait locus), we found that both SNPs are significantly associated with the expression of NEDD9 in peripheral blood samples (20), indicating that this susceptibility locus may be involved in the regulation of NEDD9 expression in prostate cancer. Using our published ChIP sequencing (ChIP-seq) datasets in prostate cancer cells (21), we show that the chromatin region overlapped with these variations was marked by high levels of H3K27ac and H3K4me2, suggesting that this intron region may contain a putative enhancer (named NEDD9-Int1Enh), and these two identified risk SNPs may play a role in differentially regulating the activity of this enhancer in prostate cancer cells (Fig. 1B). Moreover, NEDD9 amplifications were also commonly found in the advanced metastatic CRPC) and NEPC (11, 22), suggesting increased NEDD9 expression may be required for prostate cancer progression in a subset of patients (Fig. 1C).
Converting T to C at the rs4713266 site increases the expression of NEDD9 in prostate cancer cells
To identify proper cell line models for the subsequent studies, we genotyped a panel of commonly used prostate cancer cell line and xenograft models and found that two CRPC lines, VCaP and PC3, have predominant risk alleles (C-allele; Fig. 2A). Interestingly, VCaP cells always contain a low level of nonrisk allele (T-allele; Supplementary Fig. S2A and S2B). Examining a prostate cancer cell line and patient sample dataset (23), we found that VCaP cells contain gene amplification of NEDD9 (Fig. 2B), which appeared to preferentially amplify the risk allele. To further determine whether variations of these two SNPs may regulate NEDD9 expression, we selected CWR22-RV1 cell line (C/T heterozygous) for the subsequent gene editing studies using a series of CRISPR/Cas9 approaches. First, we made a genomic deletion of NEDD9-Int1Enh (∼2 kb) by using two lentiviral sgRNAs against the 5′ and 3′ boundaries of this enhancer in an established CWR22-RV1 cell line that expresses active Cas9 (Supplementary Fig. S3A and S3B; ref. 24). As shown in Fig. 2C, the deletion decreased the mRNA expression of NEDD9 (∼40%), indicating that this chromatin region is indeed an active enhancer regulating NEDD9 transcription. Second, to determine which SNP is the causal SNP, we performed the CRISPR activation approach by stably expressing a catalytically dead Cas9 (dCas9) fused with an activator complex (VPR) and subsequently infecting cells with a lentiviral sgRNA against rs4713266 region (sg-266), rs2018334 region (sg-334), or a nearby nonenhancer region (sg-NE, negative control). As shown in Fig. 2D, only the activator complex bound at rs4713266 region (sg-266) increased the expression (∼1.7-fold) of NEDD9, suggesting that rs4713266 but not rs2018334 is the causal SNP. Therefore, we only focused on rs4713266 for subsequent studies. Next, we directly alternated nucleotide sequence of rs4713266 in the Cas9-expressing CWR22-RV1 cell line by infecting cells with a lentiviral sgRNA against the SNP region and by cotransfecting a single-strand template DNA oligo (containing T or C), followed by the selection for stable clones containing homozygous risk alleles (C/C) or nonrisk alleles (T/T; Fig. 2E; Supplementary Fig. S3C). As shown in Fig. 2F, the “C/C” line had a noticeable increase of H3K27ac and H3K4me2 at NEDD9-Int1Enh, indicating this enhancer is more active. Importantly, the alteration from the heterozygous C/T to the homozygous C/C resulted in a significant increase of NEDD9 mRNA expression and its coded protein expression (Fig. 2G and H). Together, these results demonstrated that T to C nucleotide editing at rs4713266 can increase NEDD9 expression.
ERG preferentially activates the nonrisk allele of NEDD9-Int1Enh
The above results suggest that NEDD9-Int1Enh is an enhancer involved in the regulation of NEDD9 expression. Therefore, the nucleotide variation at rs4713266 (C versus T) may result in differential recruitment and activity of TFs. Interestingly, searching public ChIP-seq databases for known TFs in prostate cancer cells, we found that rs4713266 was overlapped with an ERG-binding site (based on ERG ChIP-seq in VCaP cell line; ref. 25), and a putative ERG-binding motif was found to match the T-allele sequence near the SNP (Fig. 3A). ERG is a member of the ETS TF family, and the overexpression of ERG in prostate cancer cells is primarily due to the chromosomal rearrangements that generate TMPRSS2-ERG fusion, which fuses the 5′ untranslated region of an androgen-regulated TMPRSS2 gene to the coding region of ERG gene (26).
To validate ERG binding, ChIP-qPCR of ERG was performed in VCaP cells (TMPRSS2-ERG positive), and ERG chromatin binding was detected at NEDD9-Int1Enh (Fig. 3B). However, this ERG binding was noticeably weaker than the previously reported ERG binding at the KLK3 enhancer. To determine whether ERG binding can be affected by T/C variation at rs4713266, we sequenced the DNA fragments that were immunoprecipitated with ERG at NEDD9-Int1Enh. As seen in Fig. 3C, although the risk allele C was predominantly found in the input DNA, the percentage of nonrisk allele T was dramatically increased in the DNA fragments amplified from ChIP-ERG, indicating that the interaction of ERG with the nonrisk allele is much stronger. However, the levels of active enhancer marks, H3K4me2 and H3K27ac, were not enriched at the nonrisk allele, suggesting the risk allele of the enhancer is also active for transcription and possibly driven by other TFs. As expected, silencing ERG in VCaP cells resulted in a modest decrease of NEDD9 expression (Fig. 3D and E).
To directly examine whether ERG binding at the T- versus C-allele could lead to differential activation of NEDD9 transcription, we cloned the DNA fragment (∼800 bp) of NEDD9-Int1Enh to contain only C or T at rs4713266 position into a luciferase reporter system (containing a minimum promoter) and then transfected the reporter together with the N-terminal–truncated ERG (the primary protein product of TMPRSS2-ERG) in ERG-negative PC3 prostate cancer cells. The basal activity of the C-allele–driven reporter was over 2-fold higher than the T-allele–driven reporter, consistent with the C-allele of the enhancer being more active (Fig. 3F). As a comparison, we also cloned the DNA fragment near rs2018334 (∼800 bp) into the reporter system, but the A to G alteration did not increase the reporter activity (Supplementary Fig. S4), further supporting that rs2018334 is not a causal SNP. Importantly, although the reporter containing the risk allele C of rs4713266 did not significantly respond to ERG expression, the reporter containing nonrisk allele T displayed a significant dose-dependent increase of activity by expressing ERG, suggesting that ERG may preferentially bind to and activate the nonrisk allele of NEDD9-Int1Enh. Moreover, we established a doxycycline-inducible HA-tagged ERG-expressing stable line (LNCaP-tetERG) in LNCaP cells (ERG-negative, T/C heterozygous) to further examine the ERG regulation on NEDD9 (Fig. 3G). The direct ERG binding at NEDD9-Int1Enh was detected by ChIP-HA when ERG expression was induced by doxycycline treatment, which also led to increased binding of Ser5 phosphorylated RNA polymerase II, an active marker for transcription initiation (Fig. 3H and I). More importantly, the expression of NEDD9 was increased approximately 2-fold by overexpression of ERG even though LNCaP cells only contain one copy of the nonrisk allele (Fig. 3J). Overall, these data highly suggest that ERG can regulate NEDD9 expression through binding to the nonrisk T allele of NEDD9-Int1Enh.
We next analyzed a large prostate cancer cohort (The Cancer Genome Atlas, TCGA; ref. 27) to determine whether NEDD9 expression could be associated with ERG fusion. In this cohort, the majority of patient samples are from men with EA, and only very few samples are from AA men. As shown in Fig. 3K, the expression of NEDD9 was significantly increased in TMPRSS2-ERG–positive prostate cancer, supporting that NEDD9 expression can be regulated by ERG. Similar results were also found from an analysis of another EA-dominant prostate cancer cohort [Memorial Sloan Kettering Cancer Center (MSKCC) prostate cancer cohort, n = 103; Supplementary Fig. S5; ref. 23]. Together, these data indicate that NEDD9 can be directly regulated by ERG in TMPRSS2-ERG–positive prostate cancer through specific binding and activation on the nonrisk T allele of NEDD9-Int1Enh.
NANOG preferentially activates the risk allele of NEDD9-Int1Enh
We next sought to identify TFs whose DNA binding may directly favor the risk C-allele of NEDD9-Int1Enh. To identify such TFs, we have conducted a motif prediction analysis using MotifDb tool and ranked TFs that may preferentially bind to the risk versus nonrisk allele based on their differential motif matching scores (Fig. 4A). The top-ranked TF is NANOG (Fig. 4B; ref. 28), which is a well-known stem cell factor and has been previously shown to regulate NEDD9 in other cancers and function to promote prostate cancer progression (7, 29, 30). To determine if NANOG can specifically activate the risk allele of NEDD9-Int1Enh, we further cloned the core fragment (∼300 bp) of NEDD9-Int1Enh into a luciferase reporter system with a minimum promoter. As shown in Fig. 4C, NANOG only increased the activity of the reporter containing the risk allele C, suggesting it can preferentially bind to and activate the risk allele of NEDD9-Int1Enh.
We then determined whether NANOG can promote the transcription of endogenous NEDD9. The protein expression of NANOG appeared to be weak in most prostate cancer cell lines that we tested except for the MDA-PCa-2b cell line (Fig. 4D). Therefore, we transiently overexpressed NANOG in the CWR22-RV1-T/T line versus -C/C line (Supplementary Fig. S6A and S6B) to compare the effect on NEDD9 expression. As shown in Fig. 4E and F, NANOG expression increased NEDD9 mRNA level in the C/C line but had very little effect on NEDD9 in the T/T line, which was in sharp contrast to the effect of overexpressing ERG that only increased NEDD9 expression in the T/T line. Because the PC3 cell line has both risk alleles (homozygous C/C) and expresses a very low level of NANOG (Fig. 4D), we also transfected PC3 cells with the NANOG-expressing vector. As shown in Fig. 4F and G, overexpression of NANOG increased NEDD9 mRNA expression for approximately 2-fold. Interestingly, PC3 cells are heterozygous for another nearby SNP (rs72827133), but it is not overlapped with the NANOG motif (see Supplementary Fig. S2A). Furthermore, silencing NANOG in the MDA-PCa-2b cell line, which is derived from an AA patient with prostate cancer, also resulted in a reduction of NEDD9 expression (Fig. 4H and I). Overall, these results indicate that NANOG can specifically regulate NEDD9 expression through preferentially binding to the rs4713266 site and activating the risk allele of NEDD9-Int1Enh.
Functional characterization of NEDD9 in prostate cancer cells
Through examining the expression of NEDD9 protein in available prostate cancer cell lines, we found that NEDD9 expression was significantly higher in VCaP cells (Fig. 5A), consistent with the amplified NEDD9 gene found in this model (23, 31). To further study the function of NEDD9 in vivo, we established VCaP stable cell lines infected by lentiviral shRNA against NEDD9 versus NTC (Fig. 5B). The ErbB2-mediated AKT activation (S473 phosphorylation) was suppressed by NEDD9 depletion (Fig. 5C), possibly due to the impairment of FAK/Src signaling as NEDD9 is a substrate of FAK/Src and the phosphorylation provides docking sites for the binding of downstream SH2-containing proteins (5). To further characterize the molecular functions and downstream signaling pathways of NEDD9 in prostate cancer, we performed an RNA-seq analysis in VCaP-shNTC and VCaP-shNEDD9 cell lines. Gene set enrichment analysis (GSEA) using hallmark gene sets indicated that NEDD9 promotes EMT, IL6/JAK/STAT3, KRAS, and IL2/STAT5 signaling pathways in prostate cancer (Fig. 5D), which are consistent with the previous studies on NEDD9 functions in other cancers (8, 32–34).
NEDD9 promotes prostate cancer tumor growth and metastasis
We next sought to determine the role of NEDD9 in prostate cancer initiation and progression. Using the transient RNAi approach, we found that silencing NEDD9 dramatically decreased VCaP cell proliferation (Fig. 6A and B). Importantly, stably silencing NEDD9 in VCaP cells markedly suppressed cell growth in vitro and xenograft tumor development in vivo (Fig. 6C and D). As several previous studies have demonstrated that NEDD9 may play a major role in tumor cell EMT, invasion, and metastasis (9, 34–37), we next determined whether NEDD9 can induce prostate cancer metastasis. As shown in Fig. 6E and F, NEDD9 silencing decreased the invasion of VCaP cells in vitro. We then examined the in vivo metastasis using a zebrafish embryo model (zebrafish do not develop an adaptive immune system until 14 days after fertilization) by injecting VCaP-shNTC or shNEDD9 cells into the zebrafish embryos. As shown in Fig. 6G, although the control VCaP cells can quickly disseminate into the blood vessel within a few hours after injection (8/10), cells with NEDD9 depletion stayed within the perivitelline space of each embryo (0/10 can metastasize), demonstrating that NEDD9 can strongly promote cancer cell intravasation, a key step for metastasis. Because the MDA-PCa-2b cell line also expresses significant levels of NEDD9 (see Fig. 5A), we next examined the function of NEDD9 using this model. Consistent with the effects found in the VCaP model, silencing NEDD9 in MDA-PCa-2b cells significantly decreased cell proliferation and migration (Fig. 6H–J). Overall, these results indicate that NEDD9 functions as an oncogene to promote prostate cancer tumor growth, invasion, and metastasis.
Our study is an attempt to address one important molecular mechanism in driving or contributing to prostate cancer initiation and progression and in part explain observed racial disparities in prostate cancer. Although SNPs associated with prostate cancer risk are commonly found within noncoding regions, the molecular functions of such SNPs are still largely unknown. This work focused on two highly related prostate cancer susceptibility SNPs at 6p24.2 that map to a putative enhancer (NEDD9-Int1Enh) of NEDD9 proto-oncogene and aimed to determine the impact of these race-associated germline variations on NEDD9 expression and activity, and to identify potential TF(s) mediating NEDD9-Int1Enh activity, NEDD9 gene transcription, and prostate cancer development. Our data strongly suggest that rs4713266 is the causal SNP that can alter NEDD9-Int1Enh activity and NEDD9 expression. Using bioinformatic analyses, we have identified a panel of candidate TFs, which have different preferences to activate the risk versus nonrisk allele of NEDD9-Int1Enh. The identified and validated TF that preferentially activates the nonrisk T allele is ERG, which is overexpressed in prostate cancer due to the TMPRSS2-ERG fusion (26). Although ERG functions to promote prostate cancer development (38, 39), it is highly debated whether its expression is correlated with aggressiveness (such as Gleason score) or outcomes of prostate cancer (40–42). Studies on ETS gene fusion in different racial groups have indicated that TMPRSS2-ERG rearrangement is less frequent in AA men (i.e., ∼10%–20% in AA vs. ∼40%–50% in EA; refs. 3, 43). This racially specific mutation frequency of ERG fusion is highly correlated with the nonrisk allele frequency of rs4713266 in men with AA (∼20%) versus EA (∼50%; see Fig. 1). Our findings strongly suggest that ERG can preferentially bind to and activate NEDD9-Int1Enh at the nonrisk allele. We have also identified NANOG as a potential TF to preferentially activate the risk allele, and NANOG has been recently reported to play an important role in driving prostate cancer progression in SPOP-mutated prostate cancer (SPOP mutations are mutually exclusive to TMPRSS2-ERG fusions; ref. 44). Interestingly, we found that the risk allele may also favor the binding of pioneer factors (MEIS1, FOXA1) that function to increase the accessibility of enhancers (45). This finding is consistent with the homozygous “C/C” line showing increased enhancer activity (see Fig. 2F). Nonetheless, our data indicate that future studies on characterizing the activities of such TFs are clearly needed. Overall, the working model we proposed in this study is that in EA patients NEDD9 expression is primarily driven by ERG through specifically activating the nonrisk T allele of NEDD9-Int1Enh, whereas in AA patients, the risk C allele, potentially activated by NANOG and/or other TFs, is driving NEDD9 expression at a comparable or even higher level to mitigate the lack of ERG fusion. Importantly, ERG-driven NEDD9 overexpression may likely be suppressed by androgen deprivation therapies (ADT) because TMPRSS2-ERG is a direct target of the androgen receptor. However, NANOG (or other TFs)-driven NEDD9 overexpression may be less affected with ADTs, which is consistent with the clinical observation that AA men, in general, do not respond well to ADTs.
Regardless of the genetic variation at NEDD9-Int1Enh, NEDD9 amplification was also commonly found in CRPC or NEPC but not in the primary prostate cancer, indicating that NEDD9 may play an important role in prostate cancer progression. Indeed, previous studies have suggested that NEDD9 functions as a major signaling molecule in driving tumor cell metastasis through regulating EMT, migration, and invasion. Using the VCaP prostate cancer cell line in which NEDD9 is overexpressed due to the gene amplification, and in its derived mouse xenograft model, we found that silencing NEDD9 resulted in a significant reduction of tumor cell invasion in vitro and suppression of the tumor growth in vivo. More importantly, using a zebrafish embryo metastasis model, we demonstrated a very strong activity of NEDD9 in promoting metastasis in vivo. These oncogenic activities of NEDD9 in prostate cancer cells are presumably mediated by the downstream pathways identified from our RNA-seq analysis, such as JAK/STAT3, IL2/STAT5, and KRAS pathways. In addition, we also observed decreased AKT activation when NEDD9 was depleted. In particular, JAK/STAT3 signaling plays an essential role in regulating EMT and metastasis in cancer (46). Nonetheless, the findings of this study will have implications in clinical therapies: while directly targeting NEDD9 may be challenging, treatments targeting the identified risk SNP-associated TFs or NEDD9-mediated signaling pathways, such as inhibitors of FAK or JAK/STAT3, may be potentially used to treat prostate cancer with AA. Overall, these data represent an important advance in our mechanistic and epidemiologic studies to address the prostate cancer disparity in AA men.
No disclosures were reported.
D. Han: Data curation, software, formal analysis, investigation, methodology, writing–original draft. J.N. Owiredu: Formal analysis, investigation, methodology. B.M. Healy: Formal analysis, investigation, methodology. M. Li: Investigation, methodology. M. Labaf: Data curation, software, formal analysis, writing–original draft. J.S. Steinfeld: Investigation, visualization, methodology, writing–review and editing. S. Patalano: Formal analysis, methodology. S. Gao: Conceptualization, supervision, methodology, writing–review and editing. M. Liu: Data curation, investigation. J.A. Macoska: Resources, supervision, project administration. K. Zarringhalam: Software, formal analysis, supervision. K.R. Siegfried: Conceptualization, resources, supervision, project administration. X. Yuan: Resources, formal analysis, investigation, writing–review and editing. T.R. Rebbeck: Conceptualization, resources, formal analysis, supervision, funding acquisition, investigation, writing–original draft, project administration, writing–review and editing. C. Cai: Conceptualization, resources, data curation, supervision, funding acquisition, investigation, writing–original draft, project administration, writing–review and editing.
This work is supported by grants from NIH (R01 CA211350 to C. Cai, P20 CA233255 to T.R. Rebbeck, and U54 CA156734 to J.A. Macoska) and U.S. Department of Defense (W81XWH-16-1-0445 and W81XWH-19-1-0361 to C. Cai, W81XWH-19-1-0777 to S. Gao, and W81XWH-15-1-0151 to X. Yuan). M. Liu and M. Labaf were supported by the graduate fellowship from Integrative Biosciences Program at University of Massachusetts Boston.
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